Become a Data Scientist: SQL, Tableau, ML & DL [4-in-1]

COURSE AUTHOR –
Start-Tech Academy

Last Updated on April 21, 2023 by GeeksGod

If you are a curious learner looking to dive into the exciting world of data science, then this course is tailor-made for you! Do you want to master the essential skills required for a successful career in data science? Are you eager to develop expertise in SQL, Tableau, Machine and Deep Learning using Python? If your answer is a resounding “yes,” then join us and embark on a journey towards becoming a data scientist!

In this course, you will gain a comprehensive understanding of SQL, Tableau, Machine Learning, and Deep Learning using Python. You will develop the necessary skills to analyze data, visualize insights, build predictive models, and derive actionable business solutions. Here are some key benefits of this course:

Develop mastery in SQL, Tableau, Machine & Deep Learning using PythonBuild strong foundations in data analysis, data visualization, and data modelingAcquire hands-on experience in working with real-world datasetsGain a deep understanding of the underlying concepts of Machine and Deep LearningLearn to build and train your own predictive models using Python

Data science is a rapidly growing field, and there is a high demand for skilled professionals who can analyze data and provide valuable insights. By learning SQL, Tableau, Machine & Deep Learning using Python, you can unlock a world of career opportunities in data science, AI, and analytics.

What’s covered in this course?

The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tools which are SQL, Tableau and Python. This will aid the students who have no prior coding background to learn and implement Analytics and Machine Learning concepts to actually solve real-world problems of Data Science.

Let me give you a brief overview of the course

Part 1 – SQL for data science

In the first section, i.e. SQL for data analytics, we will be teaching you everything in SQL that you will need for Data analysis in businesses. We will start with basic data operations like creating a table, retrieving data from a table etc. Later on, we will learn advanced topics like subqueries, Joins, data aggregation, and pattern matching.

Part 2 – Data visualization using Tableau

In this section, you will learn how to develop stunning dashboards, visualizations and insights that will allow you to explore, analyze and communicate your data effectively. You will master key Tableau concepts such as data blending, calculations, and mapping. By the end of this part, you will be able to create engaging visualizations that will enable you to make data-driven decisions confidently.

Part 3 – Machine Learning using Python

In this part, we will first give a crash course in python to get you started with this programming language. Then we will learn how to preprocess and prepare data before building a machine learning model. Once the data is ready, we will start building different regression and classification models such as Linear and logistic regression, decision trees, KNN, random forests etc.

Part 4 – Deep Learning using Python

In the last part, you will learn how to make neural networks to find complex patterns in data and make predictive models. We will also learn the concepts behind image recognition models and build a convolutional neural network for this purpose.

Throughout the course, you will work on several activities such as:

Building an SQL database and retrieving relevant data from itCreating interactive dashboards using TableauImplementing various Machine Learning algorithmsBuilding a Deep Learning model using Keras and TensorFlow

This course is unique because it covers the four essential topics for a data scientist, providing a comprehensive learning experience. You will learn from industry experts who have hands-on experience in data science and have worked with real-world datasets.

What makes us qualified to teach you?

The course is taught by Abhishek (MBA – FMS Delhi, B. Tech – IIT Roorkee) and Pukhraj (MBA – IIM Ahmedabad, B. Tech – IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of business analytics in this course. We have in-hand experience in Business Analysis.

We are also the creators of some of the most popular online courses – with over 1,200,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman – Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.

Don’t miss out on this opportunity to become a data scientist and unlock your full potential! Enroll now and start your journey towards a fulfilling career in data science.

Udemy Coupon :

718CCCB

What you will learn :

1. Develop a strong foundation in SQL and understand how to use SQL queries to manipulate and retrieve data from a database.
2. Explore the features of Tableau and learn to create interactive visualizations to effectively communicate insights to stakeholders.
3. Master the concepts of machine learning and learn to implement various machine learning algorithms using Python.
4. Discover the basics of Deep Learning and understand how to build and train a deep neural network using Keras and TensorFlow.
5. Explore techniques for data preprocessing and feature engineering, including handling missing values and encoding categorical variables
6. Master the art of model selection and evaluation, including techniques for cross-validation, hyperparameter tuning, and overfitting prevention.
7. Discover the principles of deep neural networks and learn to build and train a convolutional neural network (CNN) for image classification.
8. Explore transfer learning and understand how to fine-tune a pre-trained CNN to solve a similar problem in a different domain.

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